Optimal Operation of Integrated Energy Systems Under Uncertainties : Distributionally Robust and Stochastic Methods
Language: English
Published by Elsevier Science Sep 2023, 2023
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Neuware - Optimal Operation of Integrated Energy Systems Under Uncertainties: Distributionally Robust and Stochastic Models discusses new solutions to the rapidly emerging concerns surrounding energy usage and environmental deterioration. Integrated energy systems (IESs) are acknowledged to be a promising approach to increasing the efficiency of energy utilization by exploiting complementary (alternative) energy sources and storages. IESs show favorable performance for improving the penetration of renewable energy sources (RESs) and accelerating low-carbon transition. However, as more renewables penetrate the energy system, their highly uncertain characteristics challenge the system, with significant impacts on safety and economic issues. To this end, this book provides systematic methods to address the aggravating uncertainties in IESs from two aspects: distributionally robust optimization and online operation.
Seller Inventory # 9780443141225
- Title
- Optimal Operation of Integrated Energy Systems Under Uncertainties : Distributionally Robust and Stochastic Methods
- Author
- Bo Yang
- Publisher
- Elsevier Science Sep 2023
- Publication year
- 2023
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 0443141223
- ISBN 13
- 9780443141225
- Item weight
- 450 grams
- Dimensions
- 229x152x0 mm
Optimal Operation of Integrated Energy Systems Under Uncertainties: Distributionally Robust and Stochastic Models discusses new solutions to the rapidly emerging concerns surrounding energy usage and environmental deterioration. Integrated energy systems (IESs) are acknowledged to be a promising approach to increasing the efficiency of energy utilization by exploiting complementary (alternative) energy sources and storages. IESs show favorable performance for improving the penetration of renewable energy sources (RESs) and accelerating low-carbon transition. However, as more renewables penetrate the energy system, their highly uncertain characteristics challenge the system, with significant impacts on safety and economic issues.
To this end, this book provides systematic methods to address the aggravating uncertainties in IESs from two aspects: distributionally robust optimization and online operation.
- Presents energy scheduling, considering power, gas, and carbon markets concurrently based on distributionally robust optimization methods
- Helps readers design day-ahead scheduling schemes, considering both decision-dependent uncertainties and decision-independent uncertainties for IES
- Covers online scheduling and energy auctions by stochastic optimization methods
- Includes analytic results given to measure the performance gap between real performance and ideal performance
"Synopsis" may belong to another edition of this title.
About the Author
Zhaojian Wang received the B.Sc. degree in electrical engineering from Tianjin University, Tianjin, China, in 2013, and the Ph.D. degree in electrical engineering from Tsinghua University, Beijing, China, in 2018. From 2016 to 2017, he was a Visiting Ph.D. Student with the California Institute of Technology, Pasadena, CA, USA. From 2018 to 2020, he was a Postdoctoral Scholar with Tsinghua University. He is currently an Assistant Professor with Shanghai Jiao Tong University, Shanghai, China. His research interests include stability analysis, optimal control, microgrid planning, and game theory-based decision making in energy and power systems. He is an Associate Editor for the IEEE Systems Journal and the IET Renewable Power Generation.
Xinping Guan received the B.Sc. degree in mathematics from Harbin Normal University, Harbin, China, in 1986, and the Ph.D. degree in control science and engineering from the Harbin Institute of Technology, Harbin, China, in 1999. He is currently the Chair Professor of Shanghai Jiao Tong University, Shanghai, China, where he is also the Dean of School of Electronic, Information and Electrical Engineering, and the Director of the Key Laboratory of Systems Control and Information Processing, Ministry of Education of China. Before that, he was the Executive Director of Office of Research Management, Shanghai Jiao Tong University, a Full Professor, and the Dean of School of Electrical Engineering, Yanshan University, Qinhuangdao, China. He has authored or co-authored five research monographs, more than 200 papers in IEEE transactions and other peer-reviewed journals, and numerous conference papers. His research interests include industrial network systems, smart manufacturing, and underwater networks. As a Principal Investigator, he has finished/been working on more than 20 national key projects. He is the Leader of the prestigious Innovative Research Team of the National Natural Science Foundation of China. He is an Executive Committee Member of Chinese Automation Association Council and the Chinese Artificial Intelligence Association Council. Dr. Guan was the recipient of the Second Prize of the National Natural Science Award of China in both 2008 and 2018, First Prize of Natural Science Award from the Ministry of Education of China in both 2006 and 2016, and IEEE Transactions on Fuzzy Systems Outstanding Paper Award in 2008. He is a National Outstanding Youth honored by NSF of China, and Changjiang Scholar's by the Ministry of Education of China and State-Level Scholar of New Century Bai Qianwan Talent Program of China. He is a Fellow of IEEE.
"About the title" may belong to another edition of this title.
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